SAP data quality Lead

  • Systel,Inc.,
  • Remote or Santa Clara, California
  • 5 days ago
SAP data quality
Contract W2, Contract Corp-To-Corp, 6 Months
Depends on Experience
Work from home available

Job Description

Lead aspects we are looking for:

1. Fluent in communication who can drive  transformation project by working cross functionally across multiple business owners

2. Manager 6 - 8 member DQ offshore team

3. Knowledge of SFDC (since many of the current prioritized challenges are in SFDC)

4. Drive scope definition (currently we have a very high level scope of 100 P1 CDEs for which we need to enable DG/DQ services)

5. Design quick DQ solutions and propose alternate approaches when there are technical roadblocks

 Responsibilities:

1.Resolve data quality problems

Activities include:

Maintain list of open issues in SNOW, work with business owners to prioritize, provide updates, validate resolutions

Interact with business users, Bizapps, IT  to resolve data quality problems using techniques such as root cause analysis as well as collecting user requirements

Design DQ rules, implement and monitor quality

Lead review DQ exceptions with business, data cleansing activities

2.Provide quality assurance oversight

Activities include:

Review quality of data entry, loads, transformations, extractions, merges, or other data pipelines.

Establish and monitor service level agreements, communication protocols with business

Manage offshore DQ development & data cleaning efforts

3. Provide data quality advisory services

Activities include:

Participate in cross-functional teams and development of improvement task forces.

Assist other groups in setting up data controls to ensure data quality objectives are met

Build functional expertise in relation to data scope for the supporting business area

4. Measure data quality

Activities include:

Design, collect, analyse, and report on data quality assurance / performance metrics.

5. Manage data quality documentation

Activities include:

Define and maintain data quality standards, definitions, and models (e.g. data quality rule book, data quality scorecards, data quality financial impact, data quality team performance metrics. This may also include any documents such as checklists, guidelines, playbooks, templates, etc.)

6. Increase data quality awareness

Activities include:

Educate stakeholders on an ongoing basis to champion Data quality processes, issue management workflows, and implementation frameworks

7. Document the return on investment of data quality activities

Activities include:

Document Financial Impact of data quality issues Analyze the return on the use of quality data

Dice Id : systel
Position Id : 6815181
Originally Posted : 6 months ago
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